




'''simple docstring'''




import json
import logging
import os
import socket

import git
import numpy as np
import torch


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d -  %(message)s''',
    datefmt='''%m/%d/%Y %H:%M:%S''',
    level=logging.INFO,
)
lowercase__  							=					logging.getLogger(__name__)
def      __snake_case       (   lowercase   :							str  ):
					snake_case_	=      git.Repo(search_parent_directories=lowercase_  )
					snake_case_	=      {
					    "repo_id": str(lowercase_  ),
					    "repo_sha": str(repo.head.object.hexsha  ),
					    "repo_branch": str(repo.active_branch  ),
					}

					with open(os.path.join(lowercase_			, "git_log.json"  )			, "w"  ) as f:
										json.dump(lowercase_			, lowercase_			, indent=4  )
def      __snake_case       (   lowercase   :							List[Any]  ):




					if params.n_gpu <= 0:
										snake_case_	=      0
										snake_case_	=      -1
										snake_case_	=      True
										snake_case_	=      False
										return

					assert torch.cuda.is_available()

					logger.info("Initializing GPUs"  )
					if params.n_gpu > 1:
										assert params.local_rank != -1

										snake_case_	=      int(os.environ["WORLD_SIZE"]  )
										snake_case_	=      int(os.environ["N_GPU_NODE"]  )
										snake_case_	=      int(os.environ["RANK"]  )

										# number of nodes / node ID
										snake_case_	=      params.world_size // params.n_gpu_per_node
										snake_case_	=      params.global_rank // params.n_gpu_per_node
										snake_case_	=      True

										assert params.n_nodes == int(os.environ["N_NODES"]  )
										assert params.node_id == int(os.environ["NODE_RANK"]  )

					# local job (single GPU)
					else:
										assert params.local_rank == -1

										snake_case_	=      1
										snake_case_	=      0
										snake_case_	=      0
										snake_case_	=      0
										snake_case_	=      1
										snake_case_	=      1
										snake_case_	=      False

					# sanity checks
					assert params.n_nodes >= 1
					assert 0 <= params.node_id < params.n_nodes
					assert 0 <= params.local_rank <= params.global_rank < params.world_size
					assert params.world_size == params.n_nodes * params.n_gpu_per_node

					# define whether this is the master process / if we are in multi-node distributed mode
					snake_case_	=      params.node_id == 0 and params.local_rank == 0
					snake_case_	=      params.n_nodes > 1

					# summary
					snake_case_	=      f'''--- Global rank: {params.global_rank} - '''
					logger.info(PREFIX + "Number of nodes: %i" % params.n_nodes  )
					logger.info(PREFIX + "Node ID        : %i" % params.node_id  )
					logger.info(PREFIX + "Local rank     : %i" % params.local_rank  )
					logger.info(PREFIX + "World size     : %i" % params.world_size  )
					logger.info(PREFIX + "GPUs per node  : %i" % params.n_gpu_per_node  )
					logger.info(PREFIX + "Master         : %s" % str(params.is_master  )  )
					logger.info(PREFIX + "Multi-node     : %s" % str(params.multi_node  )  )
					logger.info(PREFIX + "Multi-GPU      : %s" % str(params.multi_gpu  )  )
					logger.info(PREFIX + "Hostname       : %s" % socket.gethostname()  )

					# set GPU device
					torch.cuda.set_device(params.local_rank  )

					# initialize multi-GPU
					if params.multi_gpu:
										logger.info("Initializing PyTorch distributed"  )
										torch.distributed.init_process_group(
										    init_method="env://"			, backend="nccl"			, )





def      __snake_case       (   lowercase   :							Union[str, Any]  ):
					np.random.seed(args.seed  )
					torch.manual_seed(args.seed  )
					if args.n_gpu > 0:
										torch.cuda.manual_seed_all(args.seed  )













'''simple docstring'''







from math import isqrt, loga


def       __UpperCamelCase					(      lowercase_       :  int   ):
       """simple docstring"""




       a_						     =			[True] * max_number
       for i in range(2   ,       isqrt(max_number - 1   ) + 1   ):
              if is_prime[i]:
                     for j in range(i**2   ,       lowercase_   ,       lowercase_   ):
                            a_						     =			False

       return [i for i in range(2   ,       lowercase_   ) if is_prime[i]]


def       __UpperCamelCase					(      lowercase_       :  int = 800_800   ,       lowercase_       :  int = 800_800   ):
       """simple docstring"""




       a_						     =			degree * loga(lowercase_   )
       a_						     =			int(lowercase_   )
       a_						     =			calculate_prime_numbers(lowercase_   )

       a_						     =			0
       a_						     =			0
       a_						     =			len(lowercase_   ) - 1
       while left < right:
              while (
                  prime_numbers[right] * loga(prime_numbers[left]   )
                  + prime_numbers[left] * loga(prime_numbers[right]   )
                  > upper_bound
              ):
                     right -= 1
              hybrid_integers_count += right - left
              left += 1

       return hybrid_integers_count


if __name__ == "__main__":
  print(f"""{solution() = }""")




